Investigating factors affecting the cost of money in banks usingData Mining

One of the potential goals of companies, including banks, is to earn profit and covercurrent expenses. Iranian banks have also been affected. The importance of calculating andunderstanding the cost of money is very important because by calculating the cost of money andanalyzing it, you can estimate and implement the amount and cost of paying bank facilities as wellas interest on deposits. Considering that the cost of money represents the correct management of theresources and costs of a bank, the investigation of ways to reduce the cost of money in state-ownedbanks can be an indicator of the efficiency of managers and the performance of a bank. The bestway to calculate the optimal cost is to use data mining techniques. In this research, decision treemodels, Bayesian rule and neural networks and RoughSet model have been analyzed using datamining methods through Weka, Rosetta and Excel software. The accuracy criterion was usingdecision tree ۴۸J (۰.۹۱۹), Bayesian theory (۰.۸۴۳), neural networks (۰.۲۷۴) and rough set model(۰.۰۹۵۲) which was in the form of law by genetic algorithm, Johnson, Holt was presented. Theserules enable bank managers to adopt policies based on the discovered models to better understandtheir resources and costs and to balance finances in their branches to achieve better value for money

کلیدواژه ها:

Cost of money ، Data Mining ، RoughSet ، Decision Tree ، Banking ، Artificial intelligence